Rainfall prediction using machine learning techniques

0Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.

Abstract

India is a farming nation and its economy is to a great extent dependent on rainforest creation. Downpour estimates are vital and fundamental for all ranchers to examine crop yields. Unsurprising rainfall is the capacity to foresee the climate with the assistance of science and innovation. It is essential to know how much rainfall to utilize water assets, horticultural creation and water arranging proficiently. Various strategies for information mining can foresee rainfall. Information extraction is utilized to appraise rainfall. This article features probably the most well-known rainfall forecast calculations. Guileless Bayes, K-Near Neighbour Algorithm, and Certificate Tree are a portion of the calculations contrasted with this record. According to a relative perspective, it is feasible to break down how rainfall is accurately anticipated.

Cite

CITATION STYLE

APA

Shabu, S. L. J., Refonaa, J., Devi, D., Aishwarya, D., Babu, K. K., & Reddy, K. P. (2024). Rainfall prediction using machine learning techniques. In AIP Conference Proceedings (Vol. 2850). American Institute of Physics. https://doi.org/10.1063/5.0208435

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free